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Randomness and learning in networks

Project description

Analysing random networks

Network analysis is a key technique in modern science. The availability of massive amounts of data and the interaction between individuals of large populations has brought network analysis to the forefront of current scientific challenges. In this context, the EU-funded RandNET project will bring together leading researchers worldwide from the areas of combinatorics, probability theory, computer science and statistics with the aim of blending approaches from these areas in the mathematical foundations for analysing random networks. As a first goal, RandNET will work to enable real applications in data science and learning on large networks. Secondly, it will establish a wide platform of knowledge dissemination on the topic of randomness and learning in networks.

Objective

Large Networks is one of the key notions in contemporary science and technology. The availability of massive amounts of data and interaction between individuals of large populations of any kind, whether biological, social or computer units, places network analysis at the forefront of current scientific challenges. The mathematical foundations of large networks have now become the focus of research in the later decades from diverse perspectives. The project RandNET brings together leading researchers worldwide from the areas of combinatorics, probability theory, computer science and statistics with the aim of blending approaches from these areas in the rigorous mathematical foundations for analysing random networks. The whole project is driven by real applications in data science and learning on large networks. This is planned through an alliance between academic and industrial partners. A second goal of the project is to establish a wide platform of knowledge dissemination on the topic of randomness and learning in networks for use of specialists from all scientific disciplines.

Fields of science (EuroSciVoc)

CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.

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Keywords

Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)

Programme(s)

Multi-annual funding programmes that define the EU’s priorities for research and innovation.

Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

MSCA-RISE - Marie Skłodowska-Curie Research and Innovation Staff Exchange (RISE)

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) H2020-MSCA-RISE-2020

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Coordinator

UNIVERSITAT POLITECNICA DE CATALUNYA
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 82 800,00
Address
CALLE JORDI GIRONA 31
08034 Barcelona
Spain

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Region
Este Cataluña Barcelona
Activity type
Higher or Secondary Education Establishments
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 142 600,00

Participants (8)

Partners (5)

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